Clean Data: The Civic Factor

The main articles are:

• Data management
• Data Quality Management

2024: Red OS Compatibility 8

Clean Data and Red Soft have confirmed the compatibility of Civil Factor and Red OS 8 products. Clean Data's data processing and standardization product will help RED OS of 8 users organize information within their organization, simplify the process of work and management decisions. Red Soft announced this on July 1, 2024.

We actively create and develop digital products in the field of data quality, including Civil Factor, so that our customers make proactive decisions when working with data and have the opportunity to use modern domestic developments for this. Compatibility with RED OS 8 is another step in this direction, because more and more organizations with which we cooperate prefer Russian operating systems. And this trend will only intensify, - said Andrey Pryanikov, Deputy General Director of Clean Data.

In the catalog of solutions compatible with RED OS, there are many domestic developments aimed at automating work with documents, storing and protecting information. Clean Data will help you prepare data for future IT implementations and significantly speed up the digitalization process, because with reference data you can avoid annoying errors or unwanted delays. We thank our colleagues from Clean Data for their fruitful cooperation! - commented Rustam Rustamov, Deputy General Director of RED SOFT.

2023: Entry into the register of domestic software

Clean Data on May 18, 2023 announced that it had registered two IT solutions for processing and standardizing data on citizens and organizations in the register of Russian software. The products are designed to speed up the provision of public services and can be used at the federal and regional levels.

The comprehensive Civil Factor product consolidates information about legal entities and individuals from different IT systems. It fixes errors in full names, addresses, phones, documents and emails. For example, he can restore the details of companies according to data from the Unified State Register of Legal Entities (USRUL), check the validity of passports and the correspondence of addresses to official directories. If the system contains incorrect data, the "Civil Factor" sends them for manual verification. Also, the Clean Data product finds duplicate records among citizens, and after checking using special algorithms, it combines them into a single reference card.

For public service delivery to become truly client-centric, it requires the consolidation of gigantic data arrays. The difficulty lies in the fact that large departments have been accumulating information for a long time and at the same time have experienced more than one change in processes. All this led to a large volume of inaccuracies. Our products help solve the problems associated with poor data quality in customer systems. The main task is not only to prevent the emergence of new erroneous data, but also to check the already accumulated ones, "said Denis Ishutinov, CEO of Clean Data.

Data processed with the help of the "Civil Factor" helps to make effective management decisions. For example, you can analyze the data of residents of the region in various sections (age, gender, financial situation) for planning socio-economic development, building kindergartens, schools, clinics. The absence of duplicate records will minimize cases of erroneous accrual of repeated social benefits. And operators of departments, having received a full card of an individual in the Civil Factor system, will be able to offer up-to-date services. So, if the information card contains information about young children, the operator will offer to enroll them in kindergarten or issue a preferential ticket to the camp.

Software Data Quality Framework also refers to the class of information resources and master data management tools ECM(,). MDM This Clean Data product provides qualitative data control at different levels and finds errors in them according to the formulated rules and criteria of checks. The Data Quality Framework can be used in any organization operating. large amount of data